class_docstr: Single shared bias used in the Double DQN paper.
  
  You can add this link after a Linear layer with nobias=True to implement a
  Linear layer with a single shared bias parameter.
  
  See http://arxiv.org/abs/1509.06461.
class_docstr_tok: ["Single","shared","bias","used","in","the","Double","DQN","paper",".","You","can","add","this","link","after","a","Linear","layer","with","nobias=True","to","implement","a","Linear","layer","with","a","single","shared","bias","parameter",".","See","http",":","\/\/arxiv.org\/abs\/1509.06461","."]
code: def __init__(self):
      super().__init__()
      self.bias = nn.Parameter(torch.zeros([1], dtype=torch.float32))
  
file_path: pfrl/examples/atari/train_dqn_ale.py
imports: import argparse
  import numpy
  import torch
  import torch.nn
  import pfrl
  from pfrl import agents, experiments, explorers
  from pfrl import nn
  from pfrl import replay_buffers, utils
  from pfrl.initializers import init_chainer_default
  from pfrl.q_functions import DiscreteActionValueHead, DuelingDQN
  from pfrl.wrappers import atari_wrappers
label_desc: Use image node_id 1 to create a new SingleSharedBias object from inherited base classes: nn with example: obj = SingleSharedBias()